Artificial intelligence is becoming part of everyday life, from online shopping recommendations to personal consultations. However, its impact within businesses remains uneven, with many organisations struggling to turn AI investments into measurable financial returns.

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According to PwC’s 29th Global CEO Survey, only 12% of CEOs have managed to extract meaningful benefits of more than 2% from AI deployment. The gap highlights a key challenge: adopting AI technology does not automatically translate into improved business performance.

One example illustrates the problem. A regional sales head at a global beverage company asks an AI assistant why sales volumes declined in the Northeast during the previous quarter. The system produces an accurate summary, pointing to reduced promotional spending and weaker convenience-store sales. However, it misses the business reason behind those figures: promotions were deliberately reduced to protect margins following a price increase.

Although the data is correct, the response lacks the context needed to support a meaningful business decision.

The central argument is that organisations need to approach AI from a business-first perspective. Instead of beginning with available data or technology, companies should first understand their goals, decision-making processes and operational priorities. Data and AI tools should then be aligned with those requirements.

The shift from experimentation to measurable returns depends on connecting AI capabilities with the real reasons behind business decisions. Without that context, even accurate AI-generated insights may have limited practical value.

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